Visual opsin gene expression evolution in the adaptive radiation of cichlid fishes of Lake Tanganyika

Tuning the visual sensory system to the ambient light is essential for survival in many animal species. This is often achieved through duplication, functional diversification, and/or differential expression of visual opsin genes. Here, we examined 753 new retinal transcriptomes from 112 species of cichlid fishes from Lake Tanganyika to unravel adaptive changes in gene expression at the macro-evolutionary and ecosystem level of one of the largest vertebrate adaptive radiations. We found that, across the radiation, all seven cone opsins – but not the rhodopsin – rank among the most differentially expressed genes in the retina, together with other vision-, circadian-rhythm-, and haemoglobin-related genes. We propose two new visual palettes characteristic of very shallow- and deep-water living species, respectively, and show that visual system adaptations along two major ecological axes, macro-habitat and diet, occur primarily via gene expression variation in a subset of cone opsin genes., In this study, we sequenced 753 new retinal transcriptomes of 112 cichlid species from African Lake Tanganyika to (i) identify adaptive changes in the expression of rod and cone visual opsin genes, (ii) define and reconstruct the evolution of visual palettes on the basis of cone opsin expression levels, and (iii) examine rod and cone opsin expression levels in relation to macro-habitat, diet, and relative eye size.
Sampling of fish eyes was performed between 2014 and 2020 at 44 locations at Lake Tanganyika covering the entire north-south axis of this approximately 670 km long lake. For each specimen, the retina of a single eye was dissected, homogenised (FastPrep-24; MP Biomedicals), and the total RNA was extracted using the Direct-zol RNA kit (Zymo) according to the manufacturer’s protocol. Individual libraries were constructed using the Illumina TruSeq stranded protocol including RiboZero Gold rRNA depletion (Illumina) and sequenced on an Illumina NovaSeq 6000 in PE 100-bp mode. Libr..., A GitHub reposit is available for further information: https://github.com/Ninet93/RNASeq_Ricci_et_al